Here Be Web Proxies
Nicholas Weaver1 , Christian Kreibich2 , Martin Dam3 , and Vern Paxson4
1

ICSI / UC San Diego 2 ICSI / Lastline
Aalborg University 4 ICSI / UC Berkeley

3

Abstract. HTTP proxies serve numerous roles, from performance enhancement
to access control to network censorship, but often operate stealthily without explicitly indicating their presence to the communicating endpoints. In this paper
we present an analysis of the evidence of proxying manifest in executions of
the ICSI Netalyzr spanning 646,000 distinct IP addresses (“clients”). To identify
proxies we employ a range of detectors at the transport and application layer,
and report in detail on the extent to which they allow us to fingerprint and map
proxies to their likely intended uses. We also analyze 17,000 clients that include
a novel proxy location technique based on traceroutes of the responses to TCP
connection establishment requests, which provides additional clues regarding the
purpose of the identified web proxies. Overall, we see 14% of Netalyzr-analyzed
clients with results that suggest the presence of web proxies.

1

Introduction

The World Wide Web continues to take center stage in people’s use of the Internet.
Indeed, for many users the web remains synonymous with the Internet itself. The plaintext nature of the web’s workhorse protocol, HTTP, makes it particularly tempting tointerpose on its flows using proxy servers, and HTTP remains one of the few protocols with explicit support for proxying. As a consequence, HTTP proxies have become
widespread and different stakeholders employ them for a wide array of reasons. To theInternet’s users, however, the actual prevalence and nature of web proxies remains aterra incognita. The typically transparent nature of web proxies means that users may
remain unaware of their existence unless the proxy significantly malfunctions or induces significant changes to the connection payload.
In this work we present the results of extensive measurements probing for the presence of web proxies by conducting HTTP connections from end-user browsers to custom web servers under our control. We do so using Netalyzr [11], which contains alarge and growing suite of proxy detection techniques. In 646,000 distinct addresses(“clients”) analyzed by Netalyzr, 14% of clients show evidence of HTTP proxying
This work is supported by the National Science Foundation under grants CNS-0831535, CNS1213157, and CNS-1223717, and the Department of Homeland Security (DHS) Science andTechnology Directorate, Cyber Security Division (DHS S&T/CSD) Broad Agency Announcement 11-02, and SPAWAR Systems Center Pacific via contract number N66001-12-C-0128,
with additional support from Amazon, Google and Comcast.

through one or more tests, suggesting that a significant fraction of all end-user HTTP
traffic passes through web proxies either on the host or in the network.
We make two contributions. First, compared to the results we presented in the original 2010 Netalyzr paper [11], we now substantially broaden both the dataset (roughly
seven times more sessions) and the depth of the analysis: we categorize the actual modifications, fingerprint proxy implementations, and, when feasible, deduce the purposeof the proxies’ presence. Second, we introduce additional testing methods, including a
proxy location technique based on traceroutes of the SYN-ACK packets responding to
TCP connection requests. Given the improved measurement apparatus, we find nearly
twice the fraction of HTTP-proxied sessions compared to our 2010 results.
We start by discussing the basic modes of operation in real-world proxies andpresenting related work (Section 2). Next, we summarize Netalyzr’s current proxydetection test suite (Section 3), followed by a detailed presentation of our proxy fingerprinting and classification methodology (Section 4). We then present our findings(Section 5), including both identified proxies as well as a set of proxies whose purpose
remains elusive, and a look at the most heavily proxied countries around the world. We
conclude with a reflection on our findings (Section 6).

2

Background and Related WorkWeb proxies examine and potentially alter some or all of a user’s HTTP request andresponse traffic, sometimes even when the user has not explicitly configured the browser
to route traffic through a particular proxy. In this work we consider both proxies colocated with the user’s computer (such as security products) as well as in-path network
elements.
Web proxies can employ two main strategies for modifying payload: TCP termination, and packet rewriting. A proxy employing TCP termination actively responds tothe browser’s TCP connection request, establishing a full transport connection with thebrowser, and creating a new, separate TCP connection with the target server. Once established, the proxy relays the content streams from both endpoints, potentially altering
them at will. While we might expect the proxy to use its own IP address for the connection to the server, some proxies reuse the client’s IP address. Doing so increases implementation complexity, but also provides transparency, and avoids any server-perceived
centralization of behavior deemed abusive because it emanates in high volume from asingle IP address.1
Packet-rewriting proxies, by contrast, modify traffic as it flows through them, potentially also injecting additional traffic, such as in the case of HTTP 404 error rewriting
we observe in some NATs in Section 5. Packet-rewriting proxies work best for tasks
that require only minor changes that can fit into a single packet, such as replacing a
response entity with a redirection script.
1

For example, BlueCoat’s knowledge base (https://kb.bluecoat.com/index?
page=content&id=KB3119&actp=RSS) specifically suggests enabling the “reflectclient-ip” configuration item (namely, use the client’s IP address rather than the proxy’s IP)
in transparent mode, when Google detects a possible abuse situation. Operators can installsuch a proxy wherever symmetric routing ensures return traffic will transit it.

A substantial body of work covers Internet censorship detection [1,15,14], focusing
on the general problem of triggering and understanding censorship mechanisms implemented using proxies or packet-injection tools.
Two academic studies have focused on specific proxy effects. The “Tripwires” workof Reis et al. [13] detected systems that modified HTTP content by performing an XMLRPC fetch and checking to see whether the returned content matched the expected content of the page itself. Huang et al. [10] used web ads in both Flash and Java to detectproxies based on flaws that make incorrect associations between hostnames and content
to cache (per CERT VU 435052, as discussed below).
Finally, Auger proposed cache-detection using timing [2], where the origin server
returns content after first observing an artificial delay. Objects that load quicker than the
delay indicate the browser must be receiving the content from a caching proxy.

3

Detecting Web Proxies

In principle we can detect the presence of a proxy any time it permutes a connection’s
properties. We base our basic detection approach on employing an HTTP client andserver under our control to exchange precisely known HTTP messages and then lookfor deviations from the expected. We implemented this approach using the ICSI Netalyzr, our popular user-driven, web-based connectivity analysis service that runs in aJava applet in the browser. See the original paper [11] for architectural and operational
details, as well as general biases in our dataset, which remain largely unchanged. Netalyzr includes a range of tests that detect proxy implementation technologies, implementation artifacts and proxy limitations. Each user-initiated test session runs througha full suite of tests, of which we now describe in detail those relevant to HTTP proxyanalysis. Since we have enhanced Netalyzr’s test suite over time, we include for eachof the test a description of the approximate number of distinct clients that observed thegiven results for the particular test.
Non-responsive Server Test (116,500 of clients tested): We expect TCPterminating proxies, unless specifically customized, to respond with a SYN-ACK toa client’s connection request before attempting to contact the client’s intended origin
server. We can test for this behavior by connecting to a server that we know will not accept the connection request [17]. For Netalyzr, we employ a server interface that sends
a RST packet in response to all incoming requests, regardless of port. If the Netalyzr
client’s attempt to connect to this server on port 80 initially succeeds, this indicates thepresence of a TCP-terminating proxy.
Proxy Traceroute (17,000 clients): The previous test indicates the presence of a
TCP-terminating proxy but does not illuminate its location. We added to Netalyzr a new
test to pinpoint the proxy’s location, as follows. For any port on which the previous test
flagged the presence of a proxy, the Netalyzr client attempts a TCP connection to our
traceroute server. Upon receipt of an incoming SYN (likely sent by an in-path proxy),
this server conducts a traceroute from server toward client using SYN-ACK packets.
This traceroute terminates upon receiving the TCP handshake’s pure ACK, rather thanan ICMP “TTL exceeded” response. We do not perform a similar test outbound fromthe client, because while the client can technically invoke commands such as traceroutedirectly, the issues of platform dependence, increased intrusiveness of the client, and thepotential lack of required user privileges for a TCP-based traceroute make this approach
problematic.
HTTP 404 Fetches (448,000 clients): While investigating DNS “error traffic monetization” [16], we discovered a proxy vendor whose product modifies HTTP 404 error responses. To detect this behavior, Netalyzr attempts to fetch three custom 404“page not found” error pages. One returns just a blank 404 page, one returns a copyof Apache’s default 404 page, and one returns Netalyzr’s custom 404 page. We thenwatch for any alterations to the content.
Previously Documented Tests. In addition to the new tests described above, we used
several existing Netalyzr tests in our analysis of web proxies.
Customized HTTP Fetch (633,000 clients): RFC 2616 [6] specifies that systems
should treat HTTP header names as case-insensitive, and, with a few exceptions, freeof ordering requirements. Netalyzr leverages these properties by implementing its own
HTTP engine and fetching a custom page from the server, using mixed-cased request
and response headers in a known order. Any changes indicate a proxy. This test also
aids in the identification of the proxy’s purpose. Some proxies declare their presence
and/or function in a header, while others may modify the HTML document or transfer
encoding in a manner which reflects the proxy’s function, or serve as a base for further
investigation (Section 4).
Non-HTTP Fetch (646,000 clients): In addition to a fetch using standard HTTP,
Netalyzr attempts to fetch an entity using the protocol declaration ICSI/1.1 instead of HTTP/1.1. A protocol-parsing proxy will likely reject this request as nonconformant.
Invalid Host Field (646,000 clients): Before Netalyzr’s release, CERT VU
435052 [9] described how some in-path proxies would interpret the Host HTTP header
and attempt to contact the listed host rather than forward the request to the intended address. We check for this vulnerability by fetching from our server with an alternate
Host header of www.google.com.
Caching and Transcoding (619,000 clients): Netalyzr twice attempts to fetch animage URL from the server using a direct request that bypasses any local browser
caching. Our server tracks first versus second requests, originally returning a particular
67kB image but for the second request returning an alternate version of the image. This
process then repeats three more times, each time with different cache-control headers.
If the client receives identical images for subsequent requests, we can deduce the presence of caching; altered images indicate transcoding. A more recent addition includes
uploading the results of any transcoded images for further analysis.
Filetype Filtering (627,000 clients): Netalyzr attempts to fetch three different filetypes (.mp3, .exe, and .torrent), each representing a type of content that some
network use policies may prohibit, and thus attempt to block with proxies.
EICAR Test Virus Filtering (296,000 clients): The initial Netalyzr release checked
for the ability to receive the EICAR [5] test “virus,” a benign program that antivirus programs recognize for testing purposes. We removed this test after receiving complaints
about security software blocking all subsequent connections.

For similar reasons we do not include censorship-triggering tests. While technicallystraightforward to implement, we cannot rule out the possibility that such a test could
result in harm to Netalyzr users who might be accused of accessing forbidden content.

4

Fingerprinting and Classifying Proxies

Using the Netalyzr results we just described, we set out to establish a methodology
for fingerprinting the detected proxies and, in a subsequent stage, classify them into
different categories of functionality.
Some of our tests naturally suggest a proxy’s purpose, such as in the case of ourcaching analysis. We combined information gathered from our measurements with amanual, iterative rule-building approach in which we establish a set of detectors for specific proxy fingerprints. In each iteration, we identified the most prevalent proxy fingerprints and used them to infer the manufacturer and/or proxy model. Sometimes this task
proved easy (such as when proxies inject a banner header, e.g., X-BlueCoat-Via);other times it required online searches and studying product whitepapers. Security andlogin gateways that block our requests generally present a page explaining their presence, while removal of whitespace suggests a transcoding proxy attempting to savebandwidth. Injected content or changes to the 404 error page also provide handy clues,
as the injected URLs either directly disclose the company involved or help us trackdown the responsible parties in discussion forums or blogs.
In total, our resulting detectors comprise 70 generic rules for policy blockers (suchas ’Blocked’ or ’Denied’ keywords) and 29 rules for individual content changes thatalter received content.

5

Identified Proxies

Our analysis identified eight categories of web proxies. We sketch each in decreasingorder of prevalence, and then discuss “dark proxies” that did not introduce any modifications that we could detect, and apparent country-wide proxies.
Antivirus (6% of clients): even though we removed the EICAR test due to collateral
damage, triggering antivirus systems remains the most prevalent type of proxy for tested
sessions. We also see indications of end-user security software through header changes
validated by web searches. For example, Fortinet software uses a local proxy that adds
an X-FCCKV2 header to HTTP requests (210 clients). Note that we do not consider
antivirus-blocking alone as an indicator of a proxy for other measurements; we only
count sessions in which the HTTP connections exhibit evidence of proxying.
Caches (2.3% of clients): HTTP caches represent the second-most frequent proxytype. These systems attempt to reduce an ISP’s upstream bandwidth by returning locallycached content instead of fetching it from origin servers. Since web clients possess theirown cache, this only saves bandwidth on popular content.
Security and Censor Proxies (0.55% of clients): We detect two popular models
of security proxies through the Via headers they inject. 1,156 clients indicate an IronPort/Cisco Web Security Appliance; 631 clients indicate a McAfee Web Gateway. Bothproxies attempt to prevent attacks against web clients.

Similarly, the BlueCoat web filter, evident in 1,993 clients, can act as a security
gateway (filtering dangerous content), an employee web-surfing censor, and/or a login
gateway. This proxy inserts a X-BlueCoat-Via header in traffic to the server, whilechanges to the reply traffic consists of just a capitalization change in the Connection
header and header reordering.
Finally, we received a session run by a volunteer behind a McAfee Smartfilter (operating as a censor) deployed in a Middle Eastern country. This proxy added a Via:
Webcat-Skein request header and reordered and changed the capitalization on theConnection, Host, and Cookie headers, yet induced no reply header changes. We
see 87 clients with this fingerprint.
Transcoding (0.54% of clients): While caches save upstream bandwidth, transcoding [7,8] conserves downstream bandwidth by compressing data into a more compact
form. We observe three different transformations, usually applied in combination. The
first consists of altered content encoding, replacing an uncompressed response with agzip-compressed response. We observe 0.5% of clients that gzip-compress our HTTP
404 response or .exe file.
The second case, observed in 0.5% of tested clients, reflected proxies removing
whitespace in the HTML content returned by our server. These transformations preserve HTML semantics (assuming that no HTML consumer relies on newlines in therendering process). A common behavior is to compress the .exe file but newline-strip
the HTML.
Finally, we also detect image transcoding that replaces our 67kB image with asmaller version. We observe 0.2% of tested clients with such modifications, usuallypreserving reasonable quality: most transcoding resulted in images greater than 22 kB(74.3%). The most compressed replacement consisted of a 5 kB image.
404 Rewriters (0.11% of clients): “Error traffic monetization” involves ISPs attempting to leverage protocol errors as a source of revenue by masking or augmenting
the error delivery in order to include advertising [16]. While this controversial practicemost commonly involves DNS NXDOMAIN errors, at least one company, Barefruit,also offers monetization of HTTP error traffic. This system requires the use of “a proxydevice or DPI system to intercept returning HTTP errors” that the device replaces witha redirection to an advertisement-laden page.
We observe two ISPs, Mediacom (398 clients) and Bresnan(17 clients), that employ HTTP error monetization. The injected content looks identical except for the URL
structure in the contained link, suggesting that both ISPs use a common provider for the
404-redirection, though the URLs differ in structure, which may reflect the ISPs working with different vendors for the landing page that offers up the ads. We also observed
a bug in the injector: many sessions include the injected JavaScript snippet at the end of
the response headers, as the injector did not insert an additional line break to separate
the header from the injected body.
The DNS and WHOIS information for the Bresnan servers suggests that Xerocole
operates the monetization, while Mediacom redirects to Infospace servers. In both cases
these companies also provide DNS error monetization for these ISPs, suggesting either
the ISPs or the monetization services use a common equipment vendor. Mediacom appears to have discontinued this technique after a public backlash in August 2012 [3].

According to our data, Bresnan appears to have never fully deployed this system, as we
see indications of its use only among a small fraction of its users.
By leveraging Netalyzr’s ability to query the local network for UPnP-enabled
gateway devices and identify gateway device vendors [4], we can expand the analysis to proxying gateway devices. We observe that instances of the Linksys WRT110
contain 404-monetization (139 clients). This system redirects the user to http://websearch.linksys.com and does not appear to be part of the initial firmware, as
devices with a manufacturer URL of http://www.linksys.com do not perform 404monetization, while many (but not all) with a manufacturer URL of http://www.
linksysbycisco.com do. This injector simply replaces the initial payload of the
HTTP 404 response packet with a redirection, while keeping subsequent content intact.
(Indeed, we observed a case where both Mediacom’s injector (which injects a script but
doesn’t change the error code) and the Linksys injector operated on the same response!)
Login Gateways (0.075% of clients): Most login proxies operate within the private
side of a NAT, enabling them to authorize connections based on a client’s pre-NAT
address. Login proxies that reside outside of a NAT, however, require some other means
to track which clients the proxy has authorized. Some of these NAT-exterior proxies set
a global “authorized” cookie for their own domain. When a new page request arrives
from the browser, the login proxy first redirects to the authorization domain, checks forthe cookie, and if present redirects the browser back to the original page, setting a cookie
within the domain of the original page, whose presence flags subsequent requests to bepassed through unmodified. Other configurations simply require that all requests go
through a manually configured proxy. We observe 433 clients where our HTTP request
encounters blocking by such a proxy.
Content Injectors (0.055% of clients): A comparatively rare class of proxies injects JavaScript or other content into HTML documents. The most common such injector, BitDefender (an antivirus solution seen for 318 clients), did not appear in theearlier survey of Reis et al. [13]. We also observed 58 clients containing an injection of “xpopup.js”, part of the CA Personal Firewall popup-blocking suite runningon client systems, and 11 clients showing evidence of Sunbelt Popup Killer, a dated(early-to-mid 2000s) anti-popup technology. Reis et al. likewise observed the latter two
in their 2008 study [13]. Other injectors in our dataset include the privacy filter Privoxy,
a VPN system by AnchorFree (here injecting advertisements), and Bluecoat and Comodo TrustConnect security products.
Three advertising injectors that operate on free hotspot connections appear in ourdataset: Meraki toolbar,2 Ovation Networks, and Icomera. These injectors insert a reference to a JavaScript routine that creates an advertisement-laden information bar oneach page. We also observed an Indian ISP using Streamride to inject advertisements
into all HTTP connections (injectors typically trigger only selectively [13]).
Some transcoding proxies also inject scripts. For example, we recorded a session
by a vodafone.de customer that, in addition to stripping whitespace, injected a script
ups/ytchunk.js into multiple pages. Web reports provide other mentions of such
behavior, such as T-Mobile in the UK injecting a script bmi-int-js/bmi.js.
2

Meraki’s HTTP headers include: X-cool-jobs-contact: jobs+proxyball@meraki.com

Finally, we also observed an injector in SouthWest Airline’s in-flight WiFi service.
The injected toolbar conveys both flight information and branding, operating in a manner similar to the advertising injectors without third-party advertisements.
All of the above injectors can cause page loading/rendering problems. A common
problem consists of injection-bearing web pages cached by the client that later can nolonger retrieve uncached injected scripts (particularly those originally served from private or unallocated IP addresses). The host of Vodafone’s injected scripts, for example,
resides at 1.2.3.50, part of a reserved address block.
Spyware Proxies (0.036% clients): The OSSProxy.exe local proxy, part of theMarketScore software package (and considered spyware by Symantec) inserts an
X-OSSProxy header with the software version.
Dark Proxies. For 8% of all clients in our dataset, we could detect the presenceof a proxy via the non-responsive server test, changes to the HTTP headers, or diverging client addresses, but we could not identify any modifications due to the proxy. The
first of these proved the most significant: prior to including a non-responsive server
test in Netalyzr, 7% of clients show evidence of a dark proxy, while after adding thetest this percentage rose to 12%. If we consider those measurements that included thenon-responsive server test, but exclude measurements for which the proxy quickly responded to the initial SYN (≤ 5 ms), the proportion of dark proxy clients is still 9%,
indicating the likely presence of an in-network proxy on the far side of any NAT. Thus,
the majority of these “dark proxies” reside internal to the network rather than at end
systems.
Observations of dark proxies could reflect several possibilities. In settings with alogin proxy (particularly hotspots), the user may have already authenticated to the login
process prior to running Netalyzr, so the proxy at that point only relays content. Caches
or transcoders that our tests do not trigger would likewise appear “dark” (although we
expect to trigger these proxies as we provide numerous opportunities for them to cacheand transcode data), as would proxies that enforce censorship or corporate policies thatour probes did not trigger.3 In a previous interaction with a Netalyzr user, we identified
a workplace environment that uses proxies that only manifest in our measurements due
to changes in the capitalization of the Connection header. In addition, we directly
experienced one setting (the US National Science Foundation’s internal network) that
contains a proxy visible only via the non-responsive server and SYN-ACK traceroutetests, which locate the proxy in the same network. In both cases, the proxies’ purpose
was confirmed by visiting “forbidden” sites.
For the dark proxy clients where the connections arrived at the server from the same
IP address as non-HTTP traffic, and for which we possess SYN-ACK traceroute results(1,345 clients), we attempted to determine the proxy’s location via the traceroute data.
We examined the last hop before the ACK-responding system in the traceroutes for both80/tcp and for a non-standard port (1947/tcp). We considered these different if the last
hop showed a different IP address; or, if one or both of the traceroutes failed to report thelast hop, the hop count differed. Of the clients measured, 13% had a different traceroute3

For our purposes, whether such systems block “bad ideas” or “malicious content”, from a
network viewpoint they appear identical unless triggered.

for the two ports, suggesting that the proxy resides in the public network rather than ator inside any NAT.
Finally, regarding the possibility of dark proxies reflecting censorship proxies, wenote some suggestive geography relating to the 197 clients that only manifested alteredcapitalization of the Connection header. When geolocalizing the IP addresses ofthese sessions (using MaxMind’s GeoLite database), 113 resided in the United States(out of 147,000 total US clients), 20 in Kuwait (out of 223 clients), and 12 in Iran (outof 196 clients).
Country-level Proxies. Our data also show evidence in some cases of potential
country-level proxying, where most or all of a nation’s traffic passes through proxies.
We examined all countries containing ≥ 50 distinct clients. Of these, the five with thehighest prevalence of proxies are Bahrain (95%), Singapore (85%), Lebanon (79%), theUnited Arab Emirates (62%), and Thailand (48%).
Bahrain: While almost all Bahraini clients exhibited proxying, far fewer (42%) exhibited caching. The proxying very likely reflects censorship, as 86% of clients thatsuccessfully performed the customized HTTP fetch detected BlueCoat in the network,
which has been previously linked to censorship in the Middle East [12].
Singapore: Again, a significantly lower percentage (26%) of clients manifest caching. Although we were unable to identify a common product by name,
we noted that many Singapore clients reside behind a proxy that only adds an
X-Forwarded-For header.
Lebanon: We suspect that the proxies we detect in Lebanon represent censors, as
only 29% manifest caching. A common motif (51% of clients) is the addition of a
Cache-Control header (even though almost no sessions actually exhibit caching),
perhaps a Via header, and downcasing the Connection header on requests.
United Arab Emirates: Unlike the previous countries, the UAE manifests a higher
degree of caching (41%), but 39% of clients also evince use of BlueCoat.
Thailand: Thailand shows a low degree of caching (17% of clients). There are also
two somewhat common products, one (15% of clients) downcases all request headers,
while the other (11%) adds a Via header.
Kenya: A single traceroute measurement to a client in Kenya indicates an apparent
backbone-level cache. In the measurement session, an HTTP traceroute from our serverto the client terminates after 82.178.159.110 rather than continuing to the next hop
taken by a non-HTTP traceroute, 196.207.31.146. AS-level information for theseaddresses indicates that they bridge the borders of Kenya and Oman.

6

Conclusion

Web proxies affect a significant fraction of Internet connections. Netalyzr’s rich proxydetection suite highlights proxies in 14% of the clients from which we have collected
measurements to date—a significant increase from our 2010 result of 8%, which we
attribute primarily to the significantly enhanced resolution of Netalyzr’s proxy detection
capabilities.
In addition to detecting the presence of proxies, we can often infer their of including
caching, transcoding, login gateways, 404-rewriting, several types of content injection,and local antivirus and spyware functionality. For those we cannot identify, we can still
identify the network location as either at/within a NAT near the browser, or further
upstream in the network. We can also detect and locate (but not classify) censorshipproxies that terminate our HTTP connections.
At the country level, we find that Bahrain, Singapore, Lebanon, the United ArabEmirates, and Thailand all extensively manifest the use of proxies, with rates from 48%
to 95%. Many of these do not appear to provide caching functionality, leaving nationwide censorship as a likely explanation.

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